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Employment type in the employer’s posting: Full timeFrom the employer’s posting
Design, build, test, deploy and maintain batch and near-real-time data pipelines
Build and maintain data processing for commissions calculations, including rules and rates
Implement automated data quality checks, controls, alerts and exception handling
Monitor production pipelines, investigate failures and data discrepancies
Implement reusable data models and curated datasets aligned with enterprise standards
Design, build, test, deploy, and maintain batch and near-real-time data pipelines on the UDP platform.
Build and maintain data processing for commissions calculations, including rules, rates, adjustments, incentives, deductions, and calculation outputs.
Implement automated data quality checks, controls, alerts, and exception handling.
Monitor production pipelines, investigate failures and data discrepancies, and provide operational support.
Implement reusable data models and curated datasets aligned with enterprise and UDP standards.
Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 2
Early. Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
23 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Who we are looking for: · Strong hands-on experience with Python, SQL, Databricks, Spark, and data pipeline development. · Experience designing ETL/ELT solutions, data models, transformations, and workflow orchestration.
· Good understanding of data quality, observability, lineage, metadata, data contracts, and access controls. · Experience with Delta Lake, Unity Catalog, Git, automated testing, CI/CD, and cloud data platforms. · Understanding of APIs, file-based integration, event processing, and secure data exchange.
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Prudential’s purpose is to be partners for every life and protectors for every future. Our purpose encourages everything we do by creating a culture in which diversity is celebrated and inclusion assured, for our people, customers, and partners. We provide a platform for our people to do their best work and make an impact to the business, and we support our people’s career ambitions. We pledge to make Prudential a place where you can Connect, Grow, and Succeed.
In this role, you will design, build, maintain, and support data pipelines and core data capabilities on Prudential Singapore’s Unified Data Platform (UDP). You will deliver reliable and auditable data products supporting business operations, analytics, AI, and commissions calculations.Job Description:
· Design, build, test, deploy, and maintain batch and near-real-time data pipelines on the UDP platform.
· Develop data ingestion, transformation, enrichment, reconciliation, and publishing processes.
· Build and maintain data processing for commissions calculations, including rules, rates, adjustments, incentives, deductions, and calculation outputs.
· Implement reusable data models and curated datasets aligned with enterprise and UDP standards.
· Ensure data accuracy, completeness, lineage, traceability, security, and auditability across pipelines and calculation processes.
· Implement automated data quality checks, controls, alerts, and exception handling.
· Optimize pipeline performance, reliability, scalability, and cost.
· Use source control, automated testing, CI/CD, environment controls, and deployment standards.
· Monitor production pipelines, investigate failures and data discrepancies, and provide operational support.
· Contribute to the enhancement and maintenance of core UDP platform capabilities, engineering standards, and reusable components.
Who we are looking for:
· Strong hands-on experience with Python, SQL, Databricks, Spark, and data pipeline development.
· Experience designing ETL/ELT solutions, data models, transformations, and workflow orchestration.
· Experience implementing complex calculation logic, reconciliation, and financial or commissions-related data processing.
· Good understanding of data quality, observability, lineage, metadata, data contracts, and access controls.
· Experience with Delta Lake, Unity Catalog, Git, automated testing, CI/CD, and cloud data platforms.
· Understanding of APIs, file-based integration, event processing, and secure data exchange.
· Good knowledge of Agile delivery, software engineering practices, and production support.
· Strong problem analysis, troubleshooting, communication, and collaboration skills.
· Insurance or financial services experience is an advantage.
Working Experience:
· At least 5 years of experience in data engineering or software engineering.
· Hands-on experience delivering and supporting production data pipelines and enterprise data platforms.
Education:
· Bachelor in Computer Science, Data Engineering, Information Systems, Engineering or equivalent.
Language:
· Fluent written and spoken English.
Prudential is an equal opportunity employer. We provide equality of opportunity of benefits for all who apply and who perform work for our organisation irrespective of sex, race, age, ethnic origin, educational, social and cultural background, marital status, pregnancy and maternity, religion or belief, disability or part-time / fixed-term work, or any other status protected by applicable law. We encourage the same standards from our recruitment and third-party suppliers taking into account the context of grade, job and location. We also allow for reasonable adjustments to support people with individual physical or mental health requirements.
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